often refers to the amount of uncertainty or risk related to the size of changes in a security's value. The higher the , the riskier the security - the price of the security can change dramatically over a short time period in either direction. A lower - security's value does not fluctuate dramatically, and tends to be more steady
This study, Volatility Bands, attempts to present a way to measure and visualize volatility, using standard deviations (σ) and indicator, and aims to point out areas that might indicate potential trading opportunities
I will try to explain the usage with examples,
same setup with different option selected
as you may observe from the examples different setting may have advantages and disadvantages over one another, it is recommended to verify a trading setup with different available options.
Additionally, It is recommended to use this indicator in conjunction with other technical indicators, or verify using chart/candle patterns. Below is an usage example using in conjunction with other indicator, in the given example “Neglected by DGT” is selected
Similarities and Differences
Bollinger Bands depicts two standard deviations above and below a , and Keltner Channel depicts two times (ATR) above and below an
Volatility Bands study combines the approach of both and Channel, with different settings and different visualization
Default settings are one standard deviations and one time (ATR) above and below 13 period . Setting can be adjusted by users but let me remind all testes are performed with the default settings.
Mathematically expressed as
Upper band area between “ema + stdev” and “ema + atr”
Lower band area between “ema – stdev” and “ema – atr”
A different display is added with the inspiration I get from one of the @quantgym ‘s study, many thanks @quantgym 😉
When difference band display is selected the study will reflect the area between “ema + stdev – atr” and “ema – stdev + atr”. As shown in the examples above
Note: standard deviation calculation can be adjusted based on price action or its moving average.
Other differentiation between BB and KC is with V-BANDS mostly we look for trade opportunities when price action move out of the bands and in most cases we assume market is consolidating when the price action is within the bands
The other indicator that presents similarities to Volatility Bands is Squeeze Indicator, which measures the relationship between and Keltner's Channels to help identify consolidations and signal when prices are likely to break out. Mainly Bands is different version of Squeeze indicator, in fact the purpose is almost same but visualization is completely different. Additionally Bands Offers trading opportunities whereas Squeeze indicator only presents market states unless a is adapted to Squeeze indicator.
Trading success is all about following your trading strategy and the indicators should fit within your trading strategy, and not to be traded upon solely
The script is for informational and educational purposes only. Use of the script does not constitute professional and/or financial advice. You alone have the sole responsibility of evaluating the script output and risks associated with the use of the script. In exchange for using the script, you agree not to hold dgtrd TradingView user liable for any possible claim for damages arising from any decision you make based on use of the script
for details of Logistic EMA you are invited to check "Logistic EMA w/ Signals by DGT" study
color of standard deviation line differentiated from atr line
- ability to view atr and stdev changes independetly
- ability to identify squeeze regions clearly
In true TradingView spirit, the author of this script has published it open-source, so traders can understand and verify it. Cheers to the author! You may use it for free, but reuse of this code in a publication is governed by House Rules. You can favorite it to use it on a chart.
- will act as oversold and overbought zones when the market is in considation period,
more importanlty and the aim of this study
- will act as entry/exit points when the price action just moves out of the bands in a trending market
in uptrend, buy when price action exits bands and sell when enters bands
and conversly in downtren, sell when price action exits bands and buy when enters bands
It is recommended to use this indicator in conjunction with other technical indicators
btw, i recognized you started publishing and started fast with valued stuff out there, congrats
if you change the multiplier factors than the behaviour will change.
if we set Standard Deviation and Volatility (ATR) Multiplier to two for example, the study will become almost same as the combination of Bollinger Bands and Keltner Channel and in this case bands can be assumed as oversold and overbought zones in a volatile market
additional info : standard deviations most known interpretation (there are some limitations/exclutions for some rare cases)
68% off all data values will fall within one standard deviation.
95% of data values will fall within two standard deviations
99.7% of all values will fall within three standard deviations
The main aim is to be able to identify the consolidation and trading zones.
I have tried to do test with different financial instruments such as stock, forex, crypto, indices etc. as well as applied on different timeframes for each.
Usage will be all about how better it fits to your tradings starategy
you may use with default setting and apply the approach stated in the description part
or try to change a bit settings either to arrange sensitivity or change its behaviour, for example
In an uptrend example you may use the bands (upper/lower ones);
to identify entry points - multipliers set to 1 (the default setting) or 0.75
to identify exit points - multipliers set to 2 or 2.25
so depending on multiplier value, the bands may act as oversold and overbought zones or considation zones (default settings)
it will be essential to practive the behaviour of the study to better fit with your trading strategy
please let me invite you to check the study that forked out of this idea and published as